MIT Sloan School of Management
Artificial Intelligence in Health Care
Discover how machine learning and artificial intelligence can be deployed in health care to overcome challenges and optimize processes.
Start date
21 April 2021
Enroll by 13 April 2021
Course duration
6 weeks
Excluding orientation
Language
English
Access resources from start date
Effort
6–8 hours per week
Self-paced learning online
Course overview
The combined percentage of surveyed health care organizations that are in some way focused on increasing their proportion of AI-assisted applications.
Accenture (Jan, 2019).
The projected value of the AI health care market by 2021.
Business News Daily (Jun, 2019).
Duration: 6 weeks (excluding orientation)
Improving prediction is one of the key challenges the medical industry faces in advancing patient care. Enhancing diagnosis, individualizing treatments, and understanding disease progression are all matters of prediction, an area where machine learning (ML) and artificial intelligence (AI) excels.1
Discover the impact AI innovations can have in medicine — on both traditional health care systems and decision-making approaches — with the Artificial Intelligence in Health Care online short course from the MIT Sloan School of Management and the MIT J-Clinic.
Through industry case studies, you’ll better understand AI’s applications and limitations, examine the challenges AI can help overcome, and explore how it’s already been successfully deployed in the sector.
You’ll gain insight and knowledge from MIT, an institution renowned for developing ML methods with applications in health care. Regina Barzilay, your Faculty Director, is also globally recognized for her work in AI and breast cancer detection.
1MIT Technology Review (Apr, 2019).Is this course for you?
Whether you work in business or medicine, this course will give you an understanding of the transformative role that AI and ML can play in the health care industry. Professionals working in the health sector will benefit from an understanding of the types of problems that AI techniques can help solve. This program covers key topics such as the basics of ML, neural networks, and deep learning. The knowledge gained throughout this course can be immediately and directly applied to roles within the health care sector.
Course overview
Introduction
Duration: 6 weeks (excluding orientation)
Improving prediction is one of the key challenges the medical industry faces in advancing patient care. Enhancing diagnosis, individualizing treatments, and understanding disease progression are all matters of prediction, an area where machine learning (ML) and artificial intelligence (AI) excels.1
Discover the impact AI innovations can have in medicine — on both traditional health care systems and decision-making approaches — with the Artificial Intelligence in Health Care online short course from the MIT Sloan School of Management and the MIT J-Clinic.
Through industry case studies, you’ll better understand AI’s applications and limitations, examine the challenges AI can help overcome, and explore how it’s already been successfully deployed in the sector.
You’ll gain insight and knowledge from MIT, an institution renowned for developing ML methods with applications in health care. Regina Barzilay, your Faculty Director, is also globally recognized for her work in AI and breast cancer detection.
1MIT Technology Review (Apr, 2019).Is this course for you?
Whether you work in business or medicine, this course will give you an understanding of the transformative role that AI and ML can play in the health care industry. Professionals working in the health sector will benefit from an understanding of the types of problems that AI techniques can help solve. This program covers key topics such as the basics of ML, neural networks, and deep learning. The knowledge gained throughout this course can be immediately and directly applied to roles within the health care sector.
What will set you apart
An AI decision framework to help you evaluate the suitability of AI technologies within your work context.
Insights into the AI opportunities available across a range of health care contexts, from hospital management to disease diagnosis.
An overview of AI and ML fundamentals, specifically through the lens of its applicability in health care.
An understanding of AI’s practical implementation and design challenges.
Knowledge of the potential of natural language processing, data analytics, and ML within health care. Course curriculum
Orientation module
Welcome to your Online Campus
Module 1
AI and machine learning — Applications and foundations
Module 2
Using AI for disease diagnosis and patient monitoring
Module 3
Natural language processing and data analytics in health care
Module 4
Interpretability in machine learning — Benefits and challenges
Module 5
Patient risk stratification and augmenting clinical workflows
Module 6
Taking an integrated approach to hospital management and optimization
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Faculty Director
Regina Barzilay
Delta Electronics Professor of Electrical Engineering and Computer Science
Earn a certificate of completion from MIT Sloan
Realize the potential of AI and ML in health care, and earn an official certificate of completion from MIT Sloan School of Management.
This program also counts towards an MIT Sloan Executive Certificate, which you can earn by completing four programs; three from your chosen certificate track and one completed in person. Find out more.
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Why choose GetSmarter?
GetSmarter, a 2U, Inc. brand, is an online learning expert with over 10 years' experience in developing high-quality online short courses from the world’s leading universities. We deliver market-led courses that equip working professionals with the expertise required for the workplace of the future. Through a data-driven approach, we analyze future skills requirements and ensure all courses address this need.
Students are supported at every stage of the learning journey, enabling them to thrive professionally through increased relevance, competence, and confidence. Find out more about GetSmarter’s approach to digital learning, course design, and online delivery here.
Payment options
You can pay your course fees before the course starts, or you may opt for a split payment plan on courses that are nine weeks and shorter. For courses 10 weeks and longer, there is a three-part payment plan available. To find out more about payment options please visit our Payment and Financing FAQ, or contact an Enrollment Adviser, to find out which option you qualify for.
Manage your time
GetSmarter's learning model is designed to help you, as a working professional, improve your skills without compromising on work and family responsibilities. The course work is broken up into weekly, manageable bite-sized modules, with incremental deadlines, designed to help you pace yourself over the duration of the course and allow you the legroom to work when it suits you best.
At the beginning of each module you'll be presented with the course content and assignments necessary for completion. You also have access to your Success Adviser who will help you manage your time, and support you with any administrative or technical queries you might have.
Seek employer assistance
By improving your skills and industry knowledge, you'll have an influence on the success of your organization. Why wouldn't you ask your boss to help you fund your studies if it's going to have an impact on the way you do business?
Of our past students, 37 percent have received financial assistance from their employers. You can ask for help, too. Here is a guide to show you how to request financial assistance from your employer.
If you are a Learning & Development (L&D) manager, or involved in training and upskilling for an organization, you can request information regarding our corporate offering on our GetSmarter for business page.
How to change your start date
As part of our commitment to your professional development, GetSmarter offers you a two-week period to change your course start date or request your money back if you’re not fully satisfied.
To qualify for a deferral of your course start date, or to cancel your enrollment and receive a refund of your course fee, your request would need to reach our Success Advisers before the release of Module 2. For more information, please read our Terms and Conditions.
Discover the Online Campus
The Online Campus will be your virtual classroom for the duration of your course. Through its easy-to-use interface you'll have access to a diverse variety of course content formats including: interactive videos, module notes, practice quizzes, presentations, assignment briefs, and additional web resources.
On the Online Campus, you'll also be able to ask questions and interact with your fellow students and teaching team through the discussion forums. If you are looking for your Online Campus login, please see the list of university partner login pages here.
